The present invention generally relates to the field of computer aided data analysis and, in particular, to the highly specialized computers capable of processing two dimensionally structured data sets, generally referred to as images, that are known as Cellular Array Processors (CAP).
In the field of image processing, the Cellular Array Processor is generally well-known as a type of computer system whose architecture is particularly suited for the task of image processing. Although the specific design may differ substantially between different implementation, the general architecture of the Cellular Array Processor is quite distinctive. Typically, a system will include a highly specialized array processor that is controlled by a control processor of conventional design. The array processor, in turn, is formed from a large number of elemental processors that are distributed as individual cells within a regular matrix. (This gives rise to the descriptive name "Cellular Array Processor".) The elemental processors are essentially identical and generally contain a function-programmable logic circuit and memory register. The programmable logic circuit is typically capable of selectively performing a limited number of primitive logic and arithmetic functions, such as "and", "or", "invert", and "rotate" on the data stored in its respective memory register in conjunction with data provided by the control processor. The control processor is linked to the elemental processors via a common instruction bus. Thus, all of the elemental processors operate separately, yet synchronously, in the performance of a common logical function on the data contained in their respective memory registers. (This is commonly referred to as Single Instruction, Multiple Data, or SIMD operation.)
Cellular Array Processor systems are particularly well suited for image processing applications, since the memory registers present in the cellular array permit the digital representation of the image to be mapped directly into the processor. Thus, the spatial interrelationship of the data within the two-dimensionally structured data set is intrinsically preserved. By directing the array processor to perform a selected sequence of SIMD logical operations corresponding to the performance of a desired image processing algorithm, the data at every point in the image can be processed essentially in parallel. Naturally, both the effective processing speed (the product of the number of instructions per second executed by an elemental processor and the number of elemental processors operating simultaneously) and the resolution of the image being processed can be increased directly by the use of additional elemental processors.
Although the Cellular Array Processor architecture is a relatively recent development within the more general field of computer aided data analysis, a substantial number of systems utilizing the architecture have been developed. While many of the systems were specifically designed for general application purposes, quite a number have been designed for considerably more specialized applications. Descriptions of a number of the general application systems can be found in S. F. Reddaway, DAP-A Distributed Processor, IEEE, Proceedings of the First Symposium on Computer Architecture, pp. 61-65 (1973), General Purpose Array Processor, U.S. Pat. No. 3,815,095 issued to Aaron H. Wester on June 4, 1974, K. E. Batcher, Array Processor, U.S. Pat. No. 3,979,728 issued to Stewart Reddaway on Sept. 7, 1976, The Massively Parallel Processor (MPP) System, AIAA, Proceedings of The Computers in Aerospace Conference 2, pp. 93-97 (1979), and Parallel Type Processor with a Stacked Auxiliary Fast Memories, U.S. Pat. No. 4,144,566 issued to Claude Timsit on Mar. 13, 1979. A number of the more specialized systems are described in Floating Point Arithmetic Unit for a Parallel Processing Computer, U.S. Pat. No. 3,701,976 issued to Richard Shivety on Oct. 31, 1972 Network Computer System, U.S. Pat. No. 4,065,808 issued to Herman Schomberg et al. on Dec. 27, 1977 and Scientific Processor, U.S. Pat. No. 4,101,960 issued to Richard Stokes et al. on July 18, 1978.
In each of these system implementations, a significantly different elemental processor design is used in order to tailor the array processors for their anticipated applications. This is principally due to the extremely wide variety of their possible applications and equally wide variety of subcomponents that can be utilized. However, a common feature of these elemental processors is that a high degree of component interconnection is used in order to optimize the elemental processor processing speed.
The particular disadvantage of using highly optimized elemental processor designs is that any significant change in the anticipated data processing application will require the elemental processors to be substantially redesigned in order to preserve the system's overall data processing capability and efficiency. This is a practical consequence of the fact that the subcomponents are too highly specialized and innerconnected to allow any significant alteration or extension of the elemental processors' component composition.